Object detection and ranging using one-dimensional radar arrays

ABSTRACT

In some aspects, a system may receive, from a first one-dimensional radar array, first information based at least in part on first reflections associated with an azimuthal plane. The system may further receive, from a second one-dimensional radar array, second information based at least in part on second reflections associated with an elevation plane. Accordingly, the system may detect an object based at least in part on the first information and may determine an elevation associated with the object based at least in part on the second information. Numerous other aspects are described.

FIELD OF THE DISCLOSURE

Aspects of the present disclosure generally relate to radar and, forexample, to object detection and ranging using one-dimensional radararrays.

BACKGROUND

Mobile stations, such as automated vehicles, drones, and otherautonomous or semi-autonomous transport devices, typically use radar(also referred to as “radio detection and ranging”) sensors in order todetect objects near the mobile stations. Generally, a mobile stationuses a directional antenna array to perform beamforming (whether analogor digital) and sweep a field-of-view (also referred to as an “FoV”)associated with the mobile station. Accordingly, the mobile station mayprocess received signals from the sweep in order to resolve locations(e.g., along an azimuthal plane), ranges, and elevations of objectswithin the FoV.

SUMMARY

In some aspects, a system for object detection includes a firstone-dimensional radar array including a plurality of first antennaelements that are arranged corresponding to a first axis along anazimuthal plane and configured to transmit first signals and receivefirst reflections based at least in part on the first signals; a secondone-dimensional radar array including a plurality of second antennaelements that are arranged corresponding to a second axis along anelevation plane and configured to transmit second signals and receivesecond reflections based at least in part on the second signals; and atleast one processor configured to detect an object based at least inpart on first information output from the first one-dimensional radararray and to determine an elevation associated with the object based atleast in part on second information output from the secondone-dimensional radar array.

In some aspects, a system for object detection includes at least oneprocessor configured to receive, from a first one-dimensional radararray, first information based at least in part on first reflectionsassociated with an azimuthal plane; receive, from a secondone-dimensional radar array, second information based at least in parton second reflections associated with an elevation plane; detect anobject based at least in part on the first information; and determine anelevation associated with the object based at least in part on thesecond information.

In some aspects, a method for object detection includes receiving, froma first one-dimensional radar array, first information based at least inpart on first reflections associated with an azimuthal plane; receiving,from a second one-dimensional radar array, second information based atleast in part on second reflections associated with an elevation plane;detecting an object based at least in part on the first information; anddetermining an elevation associated with the object based at least inpart on the second information.

In some aspects, a non-transitory computer-readable medium storing a setof instructions for wireless communication includes one or moreinstructions that, when executed by one or more processors of an objectdetection system, cause the object detection system to receive, from afirst one-dimensional radar array, first information based at least inpart on first reflections associated with an azimuthal plane; receive,from a second one-dimensional radar array, second information based atleast in part on second reflections associated with an elevation plane;detect an object based at least in part on the first information; anddetermine an elevation associated with the object based at least in parton the second information.

In some aspects, an apparatus for wireless communication includes meansfor receiving, from a first one-dimensional radar array, firstinformation based at least in part on first reflections associated withan azimuthal plane; means for receiving, from a second one-dimensionalradar array, second information based at least in part on secondreflections associated with an elevation plane; means for detecting anobject based at least in part on the first information; and means fordetermining an elevation associated with the object based at least inpart on the second information.

Aspects generally include a method, apparatus, system, computer programproduct, non-transitory computer-readable medium, user device, userequipment, wireless communication device, and/or processing system assubstantially described with reference to and as illustrated by thedrawings and specification.

The foregoing has outlined rather broadly the features and technicaladvantages of examples according to the disclosure in order that thedetailed description that follows may be better understood. Additionalfeatures and advantages will be described hereinafter. The conceptionand specific examples disclosed may be readily utilized as a basis formodifying or designing other structures for carrying out the samepurposes of the present disclosure. Such equivalent constructions do notdepart from the scope of the appended claims. Characteristics of theconcepts disclosed herein, both their organization and method ofoperation, together with associated advantages will be better understoodfrom the following description when considered in connection with theaccompanying figures. Each of the figures is provided for the purposesof illustration and description, and not as a definition of the limitsof the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the above-recited features of the present disclosure can beunderstood in detail, a more particular description, briefly summarizedabove, may be had by reference to aspects, some of which are illustratedin the appended drawings. It is to be noted, however, that the appendeddrawings illustrate only certain typical aspects of this disclosure andare therefore not to be considered limiting of its scope, for thedescription may admit to other equally effective aspects. The samereference numbers in different drawings may identify the same or similarelements.

FIG. 1 is a diagram illustrating an example environment in whichone-dimensional radar arrays described herein may be implemented, inaccordance with the present disclosure.

FIG. 2A is a diagram illustrating example components of one or moredevices shown in FIG. 1 , such as an automated vehicle, in accordancewith the present disclosure.

FIG. 2B is a diagram illustrating example components of one or moredevices shown in FIG. 1 , such as a radar, in accordance with thepresent disclosure.

FIG. 3 is a diagram illustrating an example one-dimensional radar array,in accordance with the present disclosure.

FIGS. 4, 5A, and 5B are diagrams illustrating examples associated withobject detection and ranging using one-dimensional radar arrays, inaccordance with the present disclosure.

FIG. 6 is a flowchart of an example process associated with objectdetection and ranging using one-dimensional radar arrays, in accordancewith the present disclosure.

DETAILED DESCRIPTION

Various aspects of the disclosure are described more fully hereinafterwith reference to the accompanying drawings. This disclosure may,however, be embodied in many different forms and should not be construedas limited to any specific structure or function presented throughoutthis disclosure. Rather, these aspects are provided so that thisdisclosure will be thorough and complete, and will fully convey thescope of the disclosure to those skilled in the art. Based on theteachings herein one skilled in the art should appreciate that the scopeof the disclosure is intended to cover any aspect of the disclosuredisclosed herein, whether implemented independently of or combined withany other aspect of the disclosure. For example, an apparatus may beimplemented or a method may be practiced using any number of the aspectsset forth herein. In addition, the scope of the disclosure is intendedto cover such an apparatus or method which is practiced using otherstructure, functionality, or structure and functionality in addition toor other than the various aspects of the disclosure set forth herein. Itshould be understood that any aspect of the disclosure disclosed hereinmay be embodied by one or more elements of a claim.

Autonomous vehicles (or semi-autonomous vehicles or other automatedtransport devices) have to detect and respond to objects that are nearthe vehicles. For example, an autonomous vehicle should detect andrespond to road signs (e.g., stop signs, yield signs, speed limit signs,and so on). Autonomous vehicles also have to detect and respond toobjects on roadways or other paths associated with the vehicles. Forexample, an autonomous vehicle should detect and avoid largeobstructions (e.g., fallen rocks), stopped vehicles, pedestrians, andother objects along a path of the vehicle.

In order to distinguish objects on the road (e.g., rocks, vehicles,pedestrians) from objects near the vehicle but not on the road (e.g.,signs and bridges), many autonomous vehicles use two-dimensional antennaarrays to sweep FoVs associated with the vehicles. For example, theantenna array for a vehicle may beamform (e.g., in analog or digital)and sweep a beam back-and-forth across the FoV to detect objects,determine distances of the objects from the vehicle, and estimateelevations of the objects above a ground surface (e.g., the road onwhich the vehicle is traveling). However, two-dimensional antenna arraysare expensive to manufacture, consume significant amounts of power(which is limited for an autonomous vehicle, especially when the vehicleis electric and powered by a battery), and result in higher processingoverhead to determine distances and elevations from received signals.

Reducing a quantity of antenna elements associated with an elevationplane reduces manufacturing cost, power consumption, and processingoverhead associated with the two-dimensional antenna array. However,this reduces accuracy of elevation measurements, and accurate elevationmeasurements are needed to ensure the vehicle does not try to go under abridge or other structure that has an associated clearance smaller thana height of the vehicle. Additionally, accurate elevation measurementsare needed to ensure the vehicle does not try to drive over a rock orother obstruction that is tall enough to damage the vehicle.

Some implementations described herein enable a mobile station, such asan autonomous vehicle, to use a first one-dimensional radar array toestimate distances of objects detected within an azimuthal plane and asecond one-dimensional radar array to estimate elevations of thedetected objects. The one-dimensional radar arrays can achieve higheraccuracy with less power consumption and lower processing overhead ascompared with two-dimensional radar arrays, as well as being lessexpensive to manufacture. Additionally, the one-dimensional radar arrayscan be dimensioned such that elevations for objects not within athreshold distance of a path of the mobile station (e.g., billboards,trees, and other objects not on or near a road) are not measured. As aresult, the mobile station conserves power and processing resourceswhile still determining elevations for some objects (e.g., bridges, roadsignals, and other objects on or near the road) with sufficient accuracyto protect the vehicle (e.g., from attempting to go under a bridge orother structure that has an associated clearance smaller than a heightof the vehicle or attempting to drive over a rock or other obstructionthat is tall enough to damage the vehicle, among other examples).

FIG. 1 is a diagram of an example environment 100 in which systemsand/or methods described herein may be implemented. As shown in FIG. 1 ,environment 100 may include a plurality of mobile stations, such asautomated vehicle 110 a and automated vehicle 110 b. Although thedescription herein focuses on automated vehicles, the descriptionsimilarly applies to other mobile stations, such as drones or otherautonomous or semi-autonomous transport devices. The automated vehicles110 a and 110 b may communicate with each other as well as a controller120. The controller 120 may communicate with a network 130, such thatthe automated vehicles 110 a and 110 b may receive data from andtransmit data to the network 130 via the controller 120. Additionally,or alternatively, the automated vehicles 110 a and 110 b may receivedata from and transmit data to the network 130 directly.

Accordingly, devices of environment 100 may interconnect via wiredconnections (e.g., the controller 120 may connect to the network 130 viaa wired backhaul), wireless connections (e.g., the automated vehicles110 a and 110 b may connect to the controller 120 via an over-the-air(OTA) interface, such as a Uu interface, and the automated vehicles 110a and 110 b may connect to each other via an OTA interface, such as aPC5 interface, among other examples), or a combination of wired andwireless connections (e.g., the controller 120 may connect to thenetwork 130 via a wireless backhaul in addition to or in lieu of a wiredbackhaul).

The automated vehicles 110 a and 110 b may each include a communicationdevice and/or a computing device. For example, the automated vehicles110 a and 110 b may each include a wireless communication device, amobile phone, a user equipment (UE), a laptop computer, a tabletcomputer, a gaming console, a wearable communication device (e.g., asmart wristwatch, a pair of smart eyeglasses, a head mounted display, ora virtual reality headset), or a similar type of device. As shown inFIG. 1 , the automated vehicles 110 a and 110 b may each further includeone or more sensors, such as radars 112 a and 112 b, respectively. Asshown in FIG. 1 , the radar 112 a may transmit a signal, which reflectsoff one or more external objects (e.g., object 114 a, which is anothervehicle in example 100). The reflection signal may be detected by theradar 112 a (e.g., when the radar 112 a uses at least one transceiver)and/or another receiving device, such as a separate antenna. Similarly,the radar 112 b may transmit a signal, which reflects off one or moreexternal objects (e.g., object 114 b, which is a traffic object inexample 100). The reflection signal may be detected by the radar 112 b(e.g., when the radar 112 b uses at least one transceiver) and/oranother receiving device, such as a separate antenna. Accordingly, theautomated vehicles 110 a and 110 b may use radars 112 a and 112 b,respectively, to detect and measure nearby objects. In other examples,the automated vehicle 110 a and/or the automated vehicle 110 b may useadditional radars (e.g., two radars or more) and/or other sensors (e.g.,one or more cameras and/or one or more infrared sensors, among otherexamples). In some implementations, the automated vehicle 110 a and/orthe automated vehicle 110 b may implement a system and/or method forobject detection and ranging, as described elsewhere herein.

Controller 120 may include one or more devices capable of communicatingwith the automated vehicle 110 a and the automated vehicle 110 b, suchas a base station (BS) of a cellular network, a mobile termination (MT)unit in an integrated access and backhaul (IAB) network, a distributedunit (DU) in an IAB network, a central unit (CU) in an TAB network, awireless local area network (WLAN) access point (AP), a platooningcontrol system (PCS), a road side unit (RSU), and/or another autonomousvehicle control system, among other examples. Accordingly, thecontroller 120 may include one or more devices capable of receivingcoordination and control signals from the network 130 via a backhaul.For example, the controller 120 may connect to a telecommunications corenetwork, such as a 5G next generation core network (NG Core), a LongTerm Evolution (LTE) evolved packet core (EPC), and/or another similartelecommunications core network, via the network 130. Additionally, oralternatively, the controller 120 may connect to a remote serverassociated with a fleet of autonomous vehicles, including the automatedvehicle 110 a and the automated vehicle 110 b, via the network 130. Thecontroller 120 may provide communication coverage for a particulargeographic area. In standards promulgated by the Third GenerationPartnership Project (3GPP), the term “cell” can refer to a coverage areaof a BS and/or a BS subsystem serving this coverage area, depending onthe context in which the term is used.

The number and arrangement of devices and networks shown in FIG. 1 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 1 . Furthermore, two or more devices shown in FIG. 1 maybe implemented within a single device, or a single device shown in FIG.1 may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 100 may perform one or more functions described as beingperformed by another set of devices of environment 100.

FIG. 2A is a diagram illustrating example components of a device 200, inaccordance with the present disclosure. Device 200 may correspond toautomated vehicle 110 a and/or automated vehicle 110 b. In some aspects,the automated vehicle 110 a and/or the automated vehicle 110 b may eachinclude one or more devices 200 and/or one or more components of device200. As shown in FIG. 2A, device 200 may include a bus 205, a processor210, a memory 215, a storage component 220, an input component 225, anoutput component 230, a communication interface 235, a position sensor240, an antenna array 245, a radar controller 250, and/or a drivingcontroller 255.

Bus 205 includes a component that permits communication among thecomponents of device 200. Processor 210 is implemented in hardware or acombination of hardware and software. Processor 210 is a centralprocessing unit (CPU), a graphics processing unit (GPU), an acceleratedprocessing unit (APU), a microprocessor, a microcontroller, a digitalsignal processor (DSP), a field-programmable gate array (FPGA), anapplication-specific integrated circuit (ASIC), or another type ofprocessing component. In some aspects, processor 210 includes one ormore processors capable of being programmed to perform a function.Memory 215 includes a random access memory (RAM), a read only memory(ROM), and/or another type of dynamic or static storage device (e.g., aflash memory, a magnetic memory, and/or an optical memory) that storesinformation and/or instructions for use by processor 210.

Storage component 220 stores information and/or software related to theoperation and use of device 200. For example, storage component 220 mayinclude a solid state drive (SSD), a flash memory, a RAM, a ROM and/oranother type of non-transitory computer-readable medium.

Input component 225 includes a component that permits device 200 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Output component 230 includes a component that providesoutput information from device 200 (e.g., a display, a speaker, a hapticfeedback component, and/or an audio or visual indicator).

Communication interface 235 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 200 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 235 may permit device 200to receive information from another device and/or provide information toanother device. For example, communication interface 235 may include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency interface, a universal serial bus(USB) interface, a wireless local area interface (e.g., a Wi-Fiinterface), and/or a cellular network interface.

Position sensor 240 includes a component that determines a positionassociated with the device 200. In some implementations, position sensor240 may generate a measurement of absolute position (e.g., usinginertial coordinates) associated with the device 200, or of relativeposition (e.g., with reference to a stationary point, such as a centerof Earth or a base station, and/or with reference to a surface, such asa surface of Earth) associated with the device 200. For example,position sensor 240 may include a global positioning system (GPS) globalnavigation satellite system (GNSS) device, a magnetometer, a gyroscope,an accelerometer, and/or another similar sensor.

Antenna array 245 includes a plurality of one-dimensional radar arrays(e.g., as described below in connection with FIG. 3 ). Each radar arraymay include a controller and a plurality of phase shifters that controla direction of the radar array along an associated plane. In someimplementations, antenna array 245 may include a set of antennas fortransmission and a separate set of antennas for reception within aone-dimensional radar array. As an alternative, antenna array 245 mayuse a same set of antennas for transmission and for reception within aone-dimensional radar array. Accordingly, each one-dimensional radararray within antenna array 245 may function as a transceiver.

Radar controller 250 includes a component that detects and measuresmovement of an object external to device 200. For example, radarcontroller 250 may transmit control signals to the antenna array 245 inorder to perform radio frequency radar. Radar controller 250 may receivesignals from the antenna array 245 and use the signals to determine adistance and an elevation associated with the object external to device200, as described elsewhere herein.

Driving controller 255 includes a component that determines andtransmits instructions for a driving component associated with thedevice 200. For example, driving controller 255 may receive a distanceand/or an elevation associated with an external object, from the radarcontroller 250, and determine an instruction for the driving componentbased at least in part on the distance and/or the elevation. Drivingcontroller 255 may transmit instructions to an accelerator device, abraking device, a steering device, a headlamp, a turn signal, and/oranother component associated with an autonomous transport device thatincludes the device 200.

Device 200 may perform one or more processes described herein. Device200 may perform these processes based on processor 210 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 215 and/or storage component 220. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions may be read into memory 215 and/or storagecomponent 220 from another computer-readable medium or from anotherdevice via communication interface 235. When executed, softwareinstructions stored in memory 215 and/or storage component 220 may causeprocessor 210 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry may be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, aspects described herein are notlimited to any specific combination of hardware circuitry and software.

In some aspects, device 200 includes means for performing one or moreprocesses described herein and/or means for performing one or moreoperations of the processes described herein. For example, device 200may include means for means for receiving, from a first one-dimensionalradar array, first information based at least in part on firstreflections associated with an azimuthal plane; means for receiving,from a second one-dimensional radar array, second information based atleast in part on second reflections associated with an elevation plane;means for detecting an object based at least in part on the firstinformation; and/or means for determining an elevation associated withthe object based at least in part on the second information. In someaspects, such means may include one or more components of device 200described in connection with FIG. 2A, such as bus 205, processor 210,memory 215, storage component 220, input component 225, output component230, communication interface 235, position sensor 240, antenna array245, radar controller 250, and/or driving controller 255.

The number and arrangement of components shown in FIG. 2A are providedas an example. In practice, device 200 may include additionalcomponents, fewer components, different components, or differentlyarranged components than those shown in FIG. 2A. Additionally, oralternatively, a set of components (e.g., one or more components) ofdevice 200 may perform one or more functions described as beingperformed by another set of components of device 200.

FIG. 2B is a diagram illustrating example components of a device 260, inaccordance with the present disclosure. Device 260 may be a radardevice. Device 260 may be included in device 200 of FIG. 2A.Accordingly, in some implementations, automated vehicle 110 a and/orautomated vehicle 110 b may include one or more devices 260 and/or oneor more components of device 260. As shown in FIG. 2B, device 260 mayinclude a bus 265, a processor 270, a memory 275, a modulator 280, ademodulator 285, a communication interface 290, and/or one or moreantennas 295.

Bus 265 includes a component that permits communication among thecomponents of device 260. Processor 270 is implemented in hardware or acombination of hardware and software. Processor 210 is a CPU, a GPU, anAPU, a microprocessor, a microcontroller, a DSP, a FPGA, an ASIC, oranother type of processing component. In some implementations, processor270 includes one or more processors capable of being programmed toperform a function. For example, processor 270 may transmit signals tomodulator 280 and/or antenna(s) 295 that cause transmission of one ormore radar signals. Additionally, or alternatively, processor 270 mayperform some pre-processing on received signals from demodulator 285and/or antenna(s) 295 before the pre-processed signals are sent (e.g.,via communication interface 290) to another processor (e.g., processor210 of device 200) for further processing. Memory 275 includes a RAM, aROM, and/or another type of dynamic or static storage device (e.g., aflash memory, a magnetic memory, and/or an optical memory) that storesinformation and/or instructions for use by processor 270.

Modulator 280 includes a component that generates an analog signal fortransmission (e.g., using antenna(s) 295). For example, modulator 280may encode a digital signal as an electromagnetic signal that can betransmitted OTA (e.g., by antenna(s) 295). Similarly, demodulator 285includes a component that generates a digital signal for processingbased at least in part on an analog signal (e.g., received usingantenna(s) 295). For example, demodulator 285 may decode a digitalsignal based at least in part on an electromagnetic signal that wasreceived (e.g., by antenna(s) 295). In some implementations, device 260may support beamforming such that processor 270 and/or modulator 280causes antenna(s) 295 to sweep a radio beam along an axis of anassociated plane, and demodulator 285 and/or processor 270 filtersanalog signals, from the antenna(s) 295, based at least in part on thestable frequency, such that objects near device 260 and within athreshold distance of the axis can be detected (e.g., using the Dopplereffect).

Communication interface 290 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 200 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 290 may permit device 200to receive information from another device and/or provide information toanother device. For example, communication interface 290 may include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency interface, a USB interface, awireless local area interface (e.g., a Wi-Fi interface), a cellularnetwork interface, and/or the like.

Antenna(s) 295 includes one or more antenna elements that transmitelectromagnetic signals based at least in part on analog signals and/orgenerate analog signals based at least in part on receivedelectromagnetic signals. In some implementations, antenna(s) 295 mayinclude, or may be included within, one or more antenna panels, antennagroups, sets of antenna elements, and/or antenna arrays, among otherexamples. An antenna panel, an antenna group, a set of antenna elements,and/or an antenna array may include one or more antenna elements. Anantenna panel, an antenna group, a set of antenna elements, and/or anantenna array may include a set of coplanar antenna elements and/or aset of non-coplanar antenna elements. An antenna panel, an antennagroup, a set of antenna elements, and/or an antenna array may includeantenna elements within a single housing and/or antenna elements withinmultiple housings.

Device 260 may perform one or more processes described herein. Device260 may perform these processes based on processor 270 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 275. A computer-readable medium is defined hereinas a non-transitory memory device. A memory device includes memory spacewithin a single physical storage device or memory space spread acrossmultiple physical storage devices.

Software instructions may be read into memory 275 from anothercomputer-readable medium or from another device via communicationinterface 290. When executed, software instructions stored in memory 275may cause processor 270 to perform one or more processes describedherein. Additionally, or alternatively, hardwired circuitry may be usedin place of or in combination with software instructions to perform oneor more processes described herein. Thus, aspects described herein arenot limited to any specific combination of hardware circuitry andsoftware.

In some implementations, device 260 includes means for performing one ormore processes described herein and/or means for performing one or moreoperations of the processes described herein. For example, device 260may include means for transmitting first signals and means for receivingfirst reflections based at least in part on the first signals; means fortransmitting second signals and means for receiving second reflectionsbased at least in part on the second signals; means for generating firstinformation based at least in part on the first reflections; and/ormeans for generating second information based at least in part on thesecond reflections. In some implementations, such means may include oneor more components of device 260 described in connection with FIG. 2B,such as bus 265, processor 270, memory 275, modulator 280, demodulator285, communication interface 290, and/or antenna(s) 295.

The number and arrangement of components shown in FIG. 2B are providedas an example. In practice, device 260 may include additionalcomponents, fewer components, different components, or differentlyarranged components than those shown in FIG. 2B. Additionally, oralternatively, a set of components (e.g., one or more components) ofdevice 260 may perform one or more functions described as beingperformed by another set of components of device 260.

FIG. 3 is a diagram illustrating an example 300 of a one-dimensionalradar array, in accordance with the present disclosure. As shown in FIG.3 , example 300 includes a transmitter (Tx) 301 that generates digitalsignals and/or analog signals (e.g., using a digital-to-analogconverter), using a modulator, for transmission by antenna array 303 asradio signals.

The antenna array 303 may include a plurality of antenna elementsarrayed along a single dimension. Accordingly, the antenna array 303 isone-dimensional. In example 300, the antenna array 303 both transmitsradio signals and receives reflections of those radio signals fromobjects within an FoV associated with the antenna array 303. As analternative, in some implementations, a separate set of antenna elementsarrayed along the same dimension as the antenna array 303 may receivethe reflections.

As further shown in FIG. 3 , a controller 305 may instruct a pluralityof phase shifters 307, corresponding to the plurality of antennaelements included in the antenna array 303. The phase shifters 307 maycontrol timing of transmissions from the antenna array 303 in order toform a directional beam from the antenna array 303 using superpositionof radio waves from different antenna elements in the antenna array 303.For example, FIG. 3 shows a directional beam associated with an angle(e.g., represented by 8 in example 300) from a normal vector associatedwith the antenna array 303. Accordingly, the controller 305 may delaytransmissions from antenna elements closer to the controller 305 ascompared with antenna elements further from the controller 305 such thatthe superposition of radio waves results in a directional beam as shownin FIG. 3 .

The number and arrangement of components shown in FIG. 3 are provided asan example. In practice, a one-dimensional radar array may includeadditional components, fewer components, different components, ordifferently arranged components than those shown in FIG. 3 .Additionally, or alternatively, other beamforming techniques, such asButler matrix beamforming, multiple signal classification (MUSIC)beamforming, and/or iterative sparse asymptotic minimum variance (SAMV)beamforming, among other examples, may be used by one-dimensional radararrays described herein.

As indicated above, FIG. 3 is provided as an example. Other examples maydiffer from what is described with respect to FIG. 3 .

FIG. 4 is a diagram illustrating an example 400 associated with objectdetection and ranging using one-dimensional radar arrays, in accordancewith the present disclosure. As shown in FIG. 4 , example 400 includes afirst one-dimensional radar array 403 and a second one-dimensional radararray 405. The radar arrays 403 and 405 may each be configured asdescribed above in connection with FIG. 3 . The radar arrays 403 and 405may be associated with a mobile station (e.g., affixed to a surface ofthe mobile station, such as surface 401). For example, the mobilestation may include an autonomous or semi-autonomous vehicle such thatthe surface 401 includes a bumper of the vehicle or another fixedsurface of the vehicle.

Radar array 403 may include a plurality of first antenna elements thatare arranged corresponding to a first axis along an azimuthal plane.Accordingly, as shown in FIG. 4 , radar array 403 may also be referredto as an azimuthal radar 403. The azimuthal radar 403 may be configuredto transmit first signals and receive first reflections based at leastin part on the first signals.

In some implementations, the azimuthal radar 403 is configured to scanalong the first axis by using beamforming to generate the first signals.For example, the azimuthal radar 403 may include a controller (and/oranother type of processor) that is configured to use antenna elements ofthe azimuthal radar 403 to beamform (e.g., as described above inconnection with FIG. 3 ) and to adjust the beamforming so as to change adirectionality associated with transmissions from the azimuthal radar403 in order to scan along the first axis (shown as the “Azimuth Scan”in FIG. 4 ).

In some implementations, and as shown in FIG. 4 , the azimuthal radar403 is associated with a range along the first axis and a range alongthe second axis, and the range along the first axis is larger than therange along the second axis. Accordingly, in example 400, the azimuthalradar 403 covers a portion of an FoV associated with the mobile station,where the portion is associated with an elliptical (or rectangular orother similarly shaped) projection on the azimuthal plane. Accordingly,a semi-major axis of the ellipse may correspond to the range along thefirst axis, and a semi-minor axis of the ellipse may correspond to therange along the second axis.

Radar array 405 may include a plurality of second antenna elements thatare arranged corresponding to a second axis along an elevation plane.Accordingly, as shown in FIG. 4 , radar array 405 may also be referredto as an elevation radar 405. The elevation radar 405 may be configuredto transmit second signals and receive second reflections based at leastin part on the second signal.

In some implementations, the elevation radar 405 is configured to scanalong the second axis by using beamforming to generate the secondsignals. For example, the elevation radar 405 may include a controller(and/or another type of processor) that is configured to use antennaelements of the elevation radar 405 to beamform (e.g., as describedabove in connection with FIG. 3 ) and to adjust the beamforming so as tochange a directionality associated with transmissions from the elevationradar 405 in order to scan along the second axis (shown as the“Elevation Scan” in FIG. 4 ).

In some implementations, and shown in FIG. 4 , the elevation radar 405is associated with a range along the first axis and a range along thesecond axis, and the range along the second axis is larger than therange along the first axis. Accordingly, in example 400, the elevationradar 405 covers a portion of an FoV associated with the mobile station,where the portion is associated with an elliptical (or rectangular orother similarly shaped) projection on the elevation plane. Accordingly,a semi-major axis of the ellipse may correspond to the range along thesecond axis, and a semi-minor axis of the ellipse may correspond to therange along the first axis.

As further shown in FIG. 4 , the first range associated with theazimuthal radar 403 may be larger than the first range associated withthe elevation radar 405. For example, the azimuthal radar 403 may covera larger portion of the FoV along the azimuthal plane than the elevationradar 405. Additionally, the second range associated with the azimuthalradar 403 may be smaller than the second range associated with theelevation radar 405. For example, the azimuthal radar 403 may cover asmaller portion of the FoV along the elevation plane than the elevationradar 405.

The mobile station may further include at least one processor. The atleast one processor may be at least partially integrated (e.g.,physically, virtually, and/or logically) with the controller included inthe azimuthal radar 403 and/or the controller included in the elevationradar 405. As an alternative, the at least one processor may be separate(e.g., physically, virtually, and/or logically) from the controller(s).

The at least one processor may receive, from the azimuthal radar 403,first information based at least in part on first reflections associatedwith an azimuthal plane. Similarly, the at least one processor mayreceive, from the elevation radar 405, second information based at leastin part on second reflections associated with an elevation plane. Forexample, the first information and the second information may includedigital information generated based at least in part onanalog-to-digital conversion and/or filtering of the first reflectionsand the second reflections, respectively. The first information and thesecond information may be associated with a single direction (e.g., asingle beam) or a plurality of directions (e.g., a scan performed usingmultiple beams). In some implementations, the first information and thesecond information may be associated with a synchronized time frame(e.g., based at least in part on simultaneous radio transmissions and/orscans from the azimuthal radar 403 and the elevation radar 405).

Accordingly, the at least one processor may detect an object based atleast in part on the first information output from the azimuthal radar403. For example, the at least one processor may identify brightnessand/or wavelength profiles within the first reflections in order todetect one or more objects in the FoV associated with the mobile station(e.g., “Object 1,” “Object 2,” and “Object 3” in example 400). In someimplementations, the at least one processor may also estimate a distance(e.g., from the azimuthal radar 403) associated with the object. Forexample, the at least one processor may use Doppler shifts and/or otherwavelength shifts associated with the first reflections in order toestimate the distance.

Additionally, the at least one processor may determine an elevationassociated with the object based at least in part on the secondinformation output from the elevation radar 405. For example, the atleast one processor may use Doppler shifts and/or other wavelengthshifts associated with the second reflections in order to estimate theelevation associated with the object. In some implementations, the atleast one processor may also detect the object within the secondreflections based at least in part on brightness and/or wavelengthprofiles.

In some implementations, the at least one processor may correlate theobject detected within the first reflections with the object detectedwithin the second reflections (e.g., to identify that the same object iswithin the first reflections and the second reflections). In oneexample, the at least one processor may determine a first distanceassociated with the object (e.g., using Doppler shifts and/or otherwavelength shifts) based at least in part on the first information fromthe azimuthal radar 403. Similarly, the at least one processor maydetermine a second distance associated with the object (e.g., usingDoppler shifts and/or other wavelength shifts) based at least in part onthe second information from the elevation radar 405. Accordingly, the atleast one processor may correlate the determined elevation (e.g., basedat least in part on the second information) with the object (e.g.,detected based at least in part on the first information) based at leastin part on a correspondence between the first distance and the seconddistance. For example, the at least one processor may determine that thesame object is detected within the first reflections and the secondreflections when the first distance and the second distance are within athreshold amount of distance (e.g., approximately equal and/or within amargin of error, such as 1%, 2%, and so on). Additionally, oralternatively, the at least one processor may determine that the sameobject is detected within the first reflections and the secondreflections when a difference between the first distance and the seconddistance are within a threshold amount of distance of a distance betweenthe azimuthal radar 403 and the elevation radar 405. For example, theazimuthal radar 403 and the elevation radar 405 may be affixed todifferent portions of surface 401 (or to different surfaces of themobile station) such that there is a non-zero distance between theazimuthal radar 403 and the elevation radar 405. Accordingly, the atleast one processor may determine that the same object is detectedwithin the first reflections and the second reflections when thedifference between the first distance and the second distance isapproximately equal to and/or within a margin of error (such as 1%, 2%,and so on) of the distance between the azimuthal radar 403 and theelevation radar 405.

Additionally, or alternatively, the at least one processor may correlatethe object detected within the first reflections with the objectdetected within the second reflections based at least in part ontracking the object across frames (e.g., different scanning cyclesperformed by the azimuthal radar 403 and the elevation radar 405). Forexample, the at least one processor may identify the object in a firstframe based at least in part on the first information from the azimuthalradar 403 and identify the object in a second frame, subsequent to thefirst frame, based at least in part on the first information from theazimuthal radar 403. Similarly, the at least one processor may identifythe object in the first frame based at least in part on the secondinformation from the elevation radar 405 and identify the object in thesecond frame, subsequent to the first frame, based at least in part onthe second information from the elevation radar 405. Accordingly, basedat least in part on tracking the object across the first frame and thesecond frame, the at least one processor may determine that the sameobject is detected within the first reflections and the secondreflections. For example, the at least one processor may determine thata translation of the object within the first reflections from the firstframe to the second frame is within a threshold of a translation of theobject within the second reflections from the first frame to the secondframe. In some implementations, the at least one processor may apply aspatial filter to the translation associated with the first reflectionsto estimate an expected translation associated with the secondreflections and/or apply a spatial filter to the translation associatedwith the second reflections to estimate an expected translationassociated with the first reflections. Accordingly, the at least oneprocessor may correlate the determined elevation with the object basedat least in part on the translation associated with the firstreflections being within a threshold of the expected translationassociated with the second reflections and/or the translation associatedwith the second reflections being within a threshold of the expectedtranslation associated with the first reflections.

Accordingly, the at least one processor may output (e.g., to a displayand/or other output device) the elevation for communication to a userand/or for further processing (e.g., as described below). For example,the user may be informed of the elevation associated with a bridge, arock, and/or other object detected by the mobile station. Additionallywith determining the elevation, the at least one processor may determinea set of coordinates associated with the object (e.g., in a coordinatesystem local to the mobile station, in an inertial coordinate system,and/or in a global coordinate system) based at least in part on thedistance associated with the object (e.g., estimated based at least inpart on the first information and/or the second information, asdescribed above) and the elevation associated with the object. In someimplementations, the at least one processor may output (e.g., to adisplay and/or other output device) the set of coordinates forcommunication to a user and/or for further processing (e.g., asdescribed below). For example, the user may be informed of thecoordinates associated with a bridge, a rock, and/or other objectdetected by the mobile station.

In some implementations, the at least one processor may additionallygenerate a three-dimensional mapping indicating the object based atleast in part on the set of coordinates. For example, thethree-dimensional mapping may include a point cloud or other visualrepresentation that includes the object based at least in part on theset of coordinates. In some implementations, the at least one processormay output (e.g., to a display and/or other output device) thethree-dimensional mapping for communication to a user and/or for furtherprocessing (e.g., as described below). For example, the user may viewthe three-dimensional mapping that shows a bridge, a rock, and/or otherobject detected by the mobile station.

In some implementations, in addition to or in lieu of outputting thedistance, the elevation, and/or the set of coordinates associated withthe object to the user, the at least one processor may generate aninstruction, for an automated vehicle that includes the at least oneprocessor (e.g., the mobile station), based at least in part on theelevation. For example, the at least one processor may instruct anaccelerator device, a brake device, and/or a steering device such thatthe automated vehicle drives over the object in the road when theelevation satisfies a threshold. On the other hand, the at least oneprocessor may instruct an accelerator device, a brake device, and/or asteering device such that the automated vehicle moves around the objectin the road when the elevation does not satisfy the threshold. Inanother example, the at least one processor may instruct an acceleratordevice, a brake device, and/or a steering device such that the automatedvehicle proceeds under the object (e.g., which may be a bridge or otheroverhead structure) when the elevation satisfies a threshold. On theother hand, the at least one processor may instruct an acceleratordevice, a brake device, and/or a steering device such that the automatedvehicle stops and/or changes course when the elevation does not satisfythe threshold (e.g., when the automated vehicle will not clear thebridge or other overhead structure).

As described above, the azimuthal radar 403 may cover a larger portionof the FoV along the azimuth plane than the elevation radar 405.Accordingly, in some implementations, the at least one processor maydetect an additional object based at least in part on the firstinformation from the azimuthal radar 403 and determine that theadditional object is outside a range associated with the elevation radar405 (e.g., as described below in connection with object 509 of FIG. 5A).Accordingly, the at least one processor may refrain from determining anelevation associated with the additional object based at least in parton the additional object being outside the range. As a result, the atleast one processor conserves power and computing resources by notdetermining elevations for objects whose elevations will not interferewith or affect movement of the mobile station. Additionally, the secondreflections may not even include the additional object because theelevation radar 405 covers a smaller portion of the FoV along theazimuth plane than the azimuthal radar 403. Accordingly, the at leastone processor does not waste power and computing resources attempting todetect the additional object based at least in part on the secondinformation because the at least one processor may determine that theadditional object is unlikely to be included in the second reflections.

By using techniques as described in connection with FIG. 4 , the mobilestation may use the one-dimensional azimuthal radar 403 to estimatedistances of objects within the azimuthal plane and the one-dimensionalelevation radar 405 to estimate elevations of the detected objects. Theazimuthal radar 403 and the elevation radar 405 can achieve higheraccuracy with less power consumption and lower processing overhead ascompared with two-dimensional radar arrays, as well as being lessexpensive to manufacture. Additionally, the azimuthal radar 403 and theelevation radar 405 can be dimensioned such that elevations for objectsnot within a threshold distance of a path of the mobile station are notmeasured (e.g., as described below in connection with FIGS. 5A and 5B).As a result, the mobile station conserves power and processing resourceswhile still determining elevations for some objects (e.g., bridges, roadsignals, and other objects on or near the road) with sufficient accuracyto protect the vehicle (e.g., from attempting to go under a bridge orother structure that has an associated clearance smaller than a heightof the vehicle or attempting to drive over a rock or other obstructionthat is tall enough to damage the vehicle, among other examples).

As indicated above, FIG. 4 is provided as an example. Other examples maydiffer from what is described with respect to FIG. 4 .

FIGS. 5A and 5B are diagrams illustrating examples 500 and 550,respectively, associated with object detection and ranging usingone-dimensional radar arrays, in accordance with the present disclosure.As shown in FIG. 5A, example 500 includes an automated vehicle 110 (oranother mobile station) proceeding along a road (or another path). Theautomated vehicle 110 may include a first one-dimensional radar arrangedcorresponding to a first axis along an azimuthal plane (e.g., similar toazimuthal radar 403 described above in connection with FIG. 4 ) andassociated with a portion 503 of the FoV associated with the automatedvehicle 110. Additionally, the automated vehicle 110 may include asecond one-dimensional radar arranged corresponding to a second axisalong an elevation plane (e.g., similar to elevation radar 405 describedabove in connection with FIG. 4 ) and associated with a portion 505 ofthe FoV associated with the automated vehicle 110. As shown in FIG. 5A,the portion 503 may be larger along the first axis than the portion 505,and the portion 503 may be smaller along the second axis than theportion 505. Accordingly, the automated vehicle 110 may determineelevations associated with objects on the road or within a thresholddistance of the road (e.g., object 507, which may be a road sign inexample 500) using the second one-dimensional radar while refrainingfrom determining elevations associated with objects not within thethreshold distance of the road (e.g., object 509, which may be a storesign or a billboard in example 500). Accordingly, the automated vehicle110 may use the one-dimensional radars to obtain accurate estimates ofelevations for some objects (such as object 507) while conserving powerand processing resources by not estimating elevations for other objects(such as object 509).

Example 550 of FIG. 5B similarly includes an automated vehicle 110 (oranother mobile station) proceeding along a road (or another path). Theautomated vehicle 110 may include a first one-dimensional radar arrangedcorresponding to a first axis along an azimuthal plane (e.g., similar toazimuthal radar 403 described above in connection with FIG. 4 ) andassociated with a portion 503 of the FoV associated with the automatedvehicle 110. Additionally, the automated vehicle 110 may include asecond one-dimensional radar arranged corresponding to a second axisalong an elevation plane (e.g., similar to elevation radar 405 describedabove in connection with FIG. 4 ) and associated with a portion 505 ofthe FoV associated with the automated vehicle 110. As shown in FIG. 5B,the portion 503 may be larger along the first axis than the portion 505,and the portion 503 may be smaller along the second axis than theportion 505. Accordingly, the automated vehicle 110 may determineelevations associated with objects on the road or within a thresholddistance of the road (e.g., object 551, which may be a bridge in example500) using the second one-dimensional radar. Accordingly, the automatedvehicle 110 may use the one-dimensional radars to obtain more accurateestimates of elevations for overhead objects (such as object 551) suchthat the automated vehicle 110 does not fail to clear overhead objectsdue to less accurate elevation estimates.

By using techniques as described in connection with FIGS. 5A and 5B, theautomated vehicle 110 may use a smaller portion 505 of the FoV todetermine elevations as compared with portion 503 of the FoV used todetermine distances. Accordingly, the automated vehicle 110 can achievehigher accuracy with less power consumption and lower processingoverhead as compared with using a same portion of the FoV for distancesand elevations. Additionally, as shown in FIGS. 5A and 5B, elevationsfor objects not within a threshold distance of the road are not measured(e.g., object 509 of example 500). As a result, the automated vehicle110 conserves power and processing resources while still determiningelevations for some objects (e.g., object 507 of example 500 and object551 of example 550) with sufficient accuracy to protect the vehicle(e.g., from attempting to go under the object 551 when the object 551has an associated clearance smaller than a height of the automatedvehicle 110, among other examples).

As indicated above, FIGS. 5A and 5B are provided as examples. Otherexamples may differ from what is described with respect to FIGS. 5A and5B.

FIG. 6 is a flowchart of an example process 600 associated with objectdetection and ranging using one-dimensional radar arrays. In someimplementations, one or more process blocks of FIG. 6 may be performedby a mobile station (e.g., mobile station 110). In some implementations,one or more process blocks of FIG. 6 may be performed by another deviceor a group of devices separate from or including the mobile station,such as an antenna array (e.g., antenna array 245), a radar controller(e.g., radar controller 250), and/or a driving controller (e.g., drivingcontroller 255). Additionally, or alternatively, one or more processblocks of FIG. 6 may be performed by one or more components of device200, such as bus 205, processor 210, memory 215, storage component 220,input component 225, output component 230, communication interface 235,and/or position sensor 240.

As shown in FIG. 6 , process 600 may include receiving, from a firstone-dimensional radar array (e.g., including or included in device 260),first information based at least in part on first reflections associatedwith an azimuthal plane (block 610). For example, an object detectionsystem of the mobile station may receive (e.g., using communicationinterface 235), from a first one-dimensional radar array, firstinformation based at least in part on first reflections associated withan azimuthal plane, as described herein.

As further shown in FIG. 6 , process 600 may include receiving, from asecond one-dimensional radar array (e.g., including or included indevice 260), second information based at least in part on secondreflections associated with an elevation plane (block 620). For example,the object detection system of the mobile station may receive (e.g.,using communication interface 235), from a second one-dimensional radararray, second information based at least in part on second reflectionsassociated with an elevation plane, as described herein.

As further shown in FIG. 6 , process 600 may include detecting an objectbased at least in part on the first information (block 630). Forexample, the object detection system of the mobile station may detect(e.g., using processor 210 and/or radar controller 250) an object basedat least in part on the first information, as described herein.

As further shown in FIG. 6 , process 600 may include determining anelevation associated with the object based at least in part on thesecond information (block 640). For example, the object detection systemof the mobile station may determine (e.g., using processor 210 and/orradar controller 250) an elevation associated with the object based atleast in part on the second information, as described herein.

Process 600 may include additional implementations, such as any singleimplementation or any combination of implementations described belowand/or in connection with one or more other processes describedelsewhere herein.

In a first implementation, process 600 further includes instructing(e.g., using processor 210, communication interface 235, and/or radarcontroller 250) the first one-dimensional radar array to scan along anaxis of the azimuthal plane by using beamforming to generate the firstinformation.

In a second implementation, alone or in combination with the firstimplementation, process 600 further includes instructing (e.g., usingprocessor 210, communication interface 235, and/or radar controller 250)the second one-dimensional radar array to scan along an axis of theelevation plane by using beamforming to generate the second information.

In a third implementation, alone or in combination with one or more ofthe first and second implementations, process 600 further includesdetecting (e.g., using processor 210 and/or radar controller 250) anadditional object based at least in part on the first information,determining (e.g., using processor 210 and/or radar controller 250) thatthe additional object is outside a range associated with the secondone-dimensional radar array, and refraining from determining (e.g.,using processor 210 and/or radar controller 250) an elevation associatedwith the additional object based at least in part on the additionalobject being outside the range.

In a fourth implementation, alone or in combination with one or more ofthe first through third implementations, determining the elevationassociated with the object includes determining (e.g., using processor210 and/or radar controller 250) a first distance associated with theobject based at least in part on the first information, determining(e.g., using processor 210 and/or radar controller 250) a seconddistance associated with the object based at least in part on the secondinformation, and correlating (e.g., using processor 210 and/or radarcontroller 250) the determined elevation with the object based at leastin part on a correspondence between the first distance and the seconddistance.

In a fifth implementation, alone or in combination with one or more ofthe first through fourth implementations, determining the elevationassociated with the object includes identifying (e.g., using processor210 and/or radar controller 250) the object in a first frame based atleast in part on the first information, identifying (e.g., usingprocessor 210 and/or radar controller 250) the object in a second frame,subsequent to the first frame, based at least in part on the secondinformation, and correlating (e.g., using processor 210 and/or radarcontroller 250) the determined elevation with the object based at leastin part on tracking the object across the first frame and the secondframe.

In a sixth implementation, alone or in combination with one or more ofthe first through fifth implementations, process 600 further includesdetermining (e.g., using processor 210 and/or radar controller 250) adistance associated with the object based at least in part on the firstinformation, and determining (e.g., using processor 210 and/or radarcontroller 250) a set of coordinates associated with the object based atleast in part on the distance and the elevation.

In a seventh implementation, alone or in combination with one or more ofthe first through sixth implementations, process 600 further includesgenerating (e.g., using processor 210, output component 230, and/orradar controller 250) a three-dimensional map indicating the objectbased at least in part on the set of coordinates.

In an eighth implementation, alone or in combination with one or more ofthe first through seventh implementations, process 600 further includesgenerating (e.g., using processor 210, communication interface 235,and/or driving controller 255) an instruction, for an automated vehicle,based at least in part on the elevation.

Although FIG. 6 shows example blocks of process 600, in someimplementations, process 600 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 6 . Additionally, or alternatively, two or more of theblocks of process 600 may be performed in parallel.

The following provides an overview of some Aspects of the presentdisclosure:

Aspect 1: A method for object detection, comprising: receiving, from afirst one-dimensional radar array, first information based at least inpart on first reflections associated with an azimuthal plane; receiving,from a second one-dimensional radar array, second information based atleast in part on second reflections associated with an elevation plane;detecting an object based at least in part on the first information; anddetermining an elevation associated with the object based at least inpart on the second information.

Aspect 2: The method of Aspect 1, further comprising: instructing thefirst one-dimensional radar array to scan along an axis of the azimuthalplane by using beamforming to generate the first signals.

Aspect 3: The method of any of Aspects 1 through 2, further comprising:instructing the second one-dimensional radar array to scan along an axisof the elevation plane by using beamforming to generate the secondsignals.

Aspect 4: The method of any of Aspects 1 through 3, further comprising:detecting an additional object based at least in part on the firstinformation; determining that the additional object is outside a rangeassociated with the second one-dimensional radar array; and refrainingfrom determining an elevation associated with the additional objectbased at least in part on the additional object being outside the range.

Aspect 5: The method of any of Aspects 1 through 4, wherein determiningthe elevation associated with the object comprises: determining a firstdistance associated with the object based at least in part on the firstinformation; determining a second distance associated with the objectbased at least in part on the second information; and correlating thedetermined elevation with the object based at least in part on acorrespondence between the first distance and the second distance.

Aspect 6: The method of any of Aspects 1 through 5, wherein determiningthe elevation associated with the object comprises: identifying theobject in a first frame based at least in part on the first information;identifying the object in a second frame, subsequent to the first frame,based at least in part on the second information; and correlating thedetermined elevation with the object based at least in part on trackingthe object across the first frame and the second frame.

Aspect 7: The method of any of Aspects 1 through 6, further comprising:determining a distance associated with the object based at least in parton the first information; and determining a set of coordinatesassociated with the object based at least in part on the distance andthe elevation.

Aspect 8: The method of Aspect 7, further comprising: generating athree-dimensional map indicating the object based at least in part onthe set of coordinates.

Aspect 9: The method of any of Aspects 1 through 8, further comprising:generating an instruction, for an automated vehicle, based at least inpart on the elevation.

Aspect 10: An apparatus for object detection, comprising a processor;memory coupled with the processor; and instructions stored in the memoryand executable by the processor to cause the apparatus to perform themethod of one or more of Aspects 1-9.

Aspect 11: A device for object detection, comprising a memory and one ormore processors coupled to the memory, the one or more processorsconfigured to perform the method of one or more of Aspects 1-9.

Aspect 12: An apparatus for object detection, comprising a firstone-dimensional radar array, a second one-dimensional radar array, andat least one processor configured to perform the method of one or moreof Aspects 1-9.

Aspect 13: A device for object detection, comprising a firstone-dimensional radar array, a second one-dimensional radar array, andat least one processor configured to perform the method of one or moreof Aspects 1-9.

Aspect 14: An apparatus for object detection, comprising at least onemeans for performing the method of one or more of Aspects 1-9.

Aspect 15: A non-transitory computer-readable medium storing code forobject detection, the code comprising instructions executable by aprocessor to perform the method of one or more of Aspects 1-9.

Aspect 16: A non-transitory computer-readable medium storing a set ofinstructions for object detection, the set of instructions comprisingone or more instructions that, when executed by one or more processorsof a device, cause the device to perform the method of one or more ofAspects 1-9.

The foregoing disclosure provides illustration and description, but isnot intended to be exhaustive or to limit the aspects to the preciseforms disclosed. Modifications and variations may be made in light ofthe above disclosure or may be acquired from practice of the aspects.

As used herein, the term “component” is intended to be broadly construedas hardware, firmware, and/or a combination of hardware and software. Asused herein, a processor is implemented in hardware, firmware, and/or acombination of hardware and software. It will be apparent that systemsand/or methods described herein may be implemented in different forms ofhardware, firmware, and/or a combination of hardware and software. Theactual specialized control hardware or software code used to implementthese systems and/or methods is not limiting of the aspects. Thus, theoperation and behavior of the systems and/or methods were describedherein without reference to specific software code—it being understoodthat software and hardware can be designed to implement the systemsand/or methods based, at least in part, on the description herein.

As used herein, satisfying a threshold may, depending on the context,refer to a value being greater than the threshold, greater than or equalto the threshold, less than the threshold, less than or equal to thethreshold, equal to the threshold, not equal to the threshold, or thelike.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of various aspects. In fact, many ofthese features may be combined in ways not specifically recited in theclaims and/or disclosed in the specification. Although each dependentclaim listed below may directly depend on only one claim, the disclosureof various aspects includes each dependent claim in combination withevery other claim in the claim set. As used herein, a phrase referringto “at least one of” a list of items refers to any combination of thoseitems, including single members. As an example, “at least one of: a, b,or c” is intended to cover a, b, c, a-b, a-c, b-c, and a-b-c, as well asany combination with multiples of the same element (e.g., a-a, a-a-a,a-a-b, a-a-c, a-b-b, a-c-c, b-b, b-b-b, b-b-c, c-c, and c-c-c or anyother ordering of a, b, and c).

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems and may be used interchangeably with “one or more.” Further, asused herein, the article “the” is intended to include one or more itemsreferenced in connection with the article “the” and may be usedinterchangeably with “the one or more.” Furthermore, as used herein, theterms “set” and “group” are intended to include one or more items (e.g.,related items, unrelated items, or a combination of related andunrelated items), and may be used interchangeably with “one or more.”Where only one item is intended, the phrase “only one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise. Also, as used herein, the term “or”is intended to be inclusive when used in a series and may be usedinterchangeably with “and/or,” unless explicitly stated otherwise (e.g.,if used in combination with “either” or “only one of”).

What is claimed is:
 1. A system for object detection, comprising: afirst one-dimensional radar array including a plurality of first antennaelements that are arranged corresponding to a first axis along anazimuthal plane and configured to transmit first signals and receivefirst reflections based at least in part on the first signals; a secondone-dimensional radar array including a plurality of second antennaelements that are arranged corresponding to a second axis along anelevation plane and configured to transmit second signals and receivesecond reflections based at least in part on the second signals; and atleast one processor configured to detect an object based at least inpart on first information output from the first one-dimensional radararray and to determine an elevation associated with the object based atleast in part on second information output from the secondone-dimensional radar array.
 2. The system of claim 1, wherein the firstone-dimensional radar array is configured to scan along the first axisby using beamforming to generate the first signals.
 3. The system ofclaim 1, wherein the second one-dimensional radar array is configured toscan along the second axis by using beamforming to generate the secondsignals.
 4. The system of claim 1, wherein the first one-dimensionalradar array is associated with a range along the first axis and a rangealong the second axis, and the range along the first axis is larger thanthe range along the second axis.
 5. The system of claim 1, wherein thesecond one-dimensional radar array is associated with a range along thefirst axis and a range along the second axis, and the range along thesecond axis is larger than the range along the first axis.
 6. The systemof claim 1, wherein the first one-dimensional radar array is associatedwith a first range along the first axis, the second one-dimensionalradar array is associated with a second range along the first axis, andthe first range is larger than the second range.
 7. The system of claim1, wherein the first one-dimensional radar array is associated with afirst range along the second axis, the second one-dimensional radararray is associated with a second range along the second axis, and thesecond range is larger than the first range.
 8. The system of claim 1,wherein the at least one processor is further configured to: detect anadditional object based at least in part on the first information fromthe first one-dimensional radar array; determine that the additionalobject is outside a range associated with the second one-dimensionalradar array; and refrain from determining an elevation associated withthe additional object based at least in part on the additional objectbeing outside the range.
 9. The system of claim 1, wherein the at leastone processor, to determine the elevation associated with the object, isconfigured to: determine a first distance associated with the objectbased at least in part on the first information from the firstone-dimensional radar array; determine a second distance associated withthe object based at least in part on the second information from thesecond one-dimensional radar array; and correlate the determinedelevation with the object based at least in part on a correspondencebetween the first distance and the second distance.
 10. The system ofclaim 1, wherein the at least one processor, to determine the elevationassociated with the object, is configured to: identify the object in afirst frame based at least in part on the first information from thefirst one-dimensional radar array; identify the object in a secondframe, subsequent to the first frame, based at least in part on thefirst information from the first one-dimensional radar array; andcorrelate the determined elevation with the object based at least inpart on tracking the object across the first frame and the second frame.11. The system of claim 1, wherein the at least one processor is furtherconfigured to: determine a distance associated with the object based atleast in part on the first information from the first one-dimensionalradar array; and determine a set of coordinates associated with theobject based at least in part on the distance and the elevation.
 12. Thesystem of claim 11, wherein the at least one processor is furtherconfigured to: generate a three-dimensional mapping indicating theobject based at least in part on the set of coordinates.
 13. The systemof claim 1, wherein the at least one processor is further configured to:generate an instruction, for an automated vehicle that includes thesystem, based at least in part on the elevation.
 14. A system for objectdetection, comprising: at least one processor configured to: receive,from a first one-dimensional radar array, first information based atleast in part on first reflections associated with an azimuthal plane;receive, from a second one-dimensional radar array, second informationbased at least in part on second reflections associated with anelevation plane; detect an object based at least in part on the firstinformation; and determine an elevation associated with the object basedat least in part on the second information.
 15. The system of claim 14,wherein the at least one processor is further configured to: detect anadditional object based at least in part on the first information;determine that the additional object is outside a range associated withthe second one-dimensional radar array; and refrain from determining anelevation associated with the additional object based at least in parton the additional object being outside the range.
 16. The system ofclaim 14, wherein the at least one processor, to determine the elevationassociated with the object, is configured to: determine a first distanceassociated with the object based at least in part on the firstinformation; determine a second distance associated with the objectbased at least in part on the second information; and correlate thedetermined elevation with the object based at least in part on acorrespondence between the first distance and the second distance. 17.The system of claim 14, wherein the at least one processor, to determinethe elevation associated with the object, is configured to: identify theobject in a first frame based at least in part on the first information;identify the object in a second frame, subsequent to the first frame,based at least in part on the second information; and correlate thedetermined elevation with the object based at least in part on trackingthe object across the first frame and the second frame.
 18. The systemof claim 14, wherein the at least one processor is further configuredto: determine a distance associated with the object based at least inpart on the first information; and determine a set of coordinatesassociated with the object based at least in part on the distance andthe elevation.
 19. The system of claim 18, wherein the at least oneprocessor is further configured to: generate a three-dimensional mappingindicating the object based at least in part on the set of coordinates.20. The system of claim 14, wherein the at least one processor isfurther configured to: generate an instruction, for an automated vehiclethat includes the system, based at least in part on the elevation.
 21. Amethod for object detection, comprising: receiving, from a firstone-dimensional radar array, first information based at least in part onfirst reflections associated with an azimuthal plane; receiving, from asecond one-dimensional radar array, second information based at least inpart on second reflections associated with an elevation plane; detectingan object based at least in part on the first information; anddetermining an elevation associated with the object based at least inpart on the second information.
 22. The method of claim 21, furthercomprising: instructing the first one-dimensional radar array to scanalong an axis of the azimuthal plane by using beamforming to generatethe first information.
 23. The method of claim 21, further comprising:instructing the second one-dimensional radar array to scan along an axisof the elevation plane by using beamforming to generate the secondinformation.
 24. The method of claim 21, further comprising: detectingan additional object based at least in part on the first information;determining that the additional object is outside a range associatedwith the second one-dimensional radar array; and refraining fromdetermining an elevation associated with the additional object based atleast in part on the additional object being outside the range.
 25. Themethod of claim 21, wherein determining the elevation associated withthe object comprises: determining a first distance associated with theobject based at least in part on the first information; determining asecond distance associated with the object based at least in part on thesecond information; and correlating the determined elevation with theobject based at least in part on a correspondence between the firstdistance and the second distance.
 26. The method of claim 21, whereindetermining the elevation associated with the object comprises:identifying the object in a first frame based at least in part on thefirst information; identifying the object in a second frame, subsequentto the first frame, based at least in part on the second information;and correlating the determined elevation with the object based at leastin part on tracking the object across the first frame and the secondframe.
 27. The method of claim 21, further comprising: determining adistance associated with the object based at least in part on the firstinformation; and determining a set of coordinates associated with theobject based at least in part on the distance and the elevation.
 28. Themethod of claim 27, further comprising: generating a three-dimensionalmap indicating the object based at least in part on the set ofcoordinates.
 29. The method of claim 21, further comprising: generatingan instruction, for an automated vehicle, based at least in part on theelevation.
 30. A non-transitory computer-readable medium storing a setof instructions for wireless communication, the set of instructionscomprising: one or more instructions that, when executed by one or moreprocessors of an object detection system, cause the object detectionsystem to: receive, from a first one-dimensional radar array, firstinformation based at least in part on first reflections associated withan azimuthal plane; receive, from a second one-dimensional radar array,second information based at least in part on second reflectionsassociated with an elevation plane; detect an object based at least inpart on the first information; and determine an elevation associatedwith the object based at least in part on the second information.